Highly efficient and selective extraction of gold by reduced graphene oxide

Materials capable of extracting gold from complex sources, especially electronic waste (e-waste), are needed for gold resource sustainability and effective e-waste recycling. However, it remains challenging to achieve high extraction capacity and precise selectivity if only a trace amount of gold is present along with other metallic elements . Here we report an approach based on reduced graphene oxide (rGO) which provides an ultrahigh capacity and selective extraction of gold ions present in ppm concentrations (>1000 mg of gold per gram of rGO at 1 ppm). The excellent gold extraction performance is accounted to the graphene areas and oxidized regions of rGO. The graphene areas spontaneously reduce gold ions to metallic gold, and the oxidized regions allow good dispersibility of the rGO material so that efficient adsorption and reduction of gold ions at the graphene areas can be realized. By controlling the protonation of the oxidized regions of rGO, gold can be extracted exclusively, without contamination by the other 14 co-existing elements typically present in e-waste. These findings are further exploited to demonstrate recycling gold from real-world e-waste with good scalability and economic viability, as exemplified by using rGO membranes in a continuous flow-through process.

To highlight the superior extraction capacity of rGO, we compared rGO's extraction capacity with adsorbents that showed high extraction capacity reported elsewhere. The molybdenum disulfide modified carbon nanotubes (CNT-MoS2), thiourea-modified porous aromatic framework (PAF-1-thiourea), porous porphyrin polymer (COP-180), and amyloid-like protein membrane (PTL membrane) showed a maximum capacity of 2495 mg/g to 1000 ppm Au ion, 2629 mg/g to 500 ppm Au ion, 1620 mg/g to 3000 ppm Au ion,1034 mg/g to 984.8 ppm Au ion, respectively. However, their capacity decreased dramatically to low concentration. For example, the extraction capacities to the lowest gold concentration studied in these reports are 1000 mg/g to 100 ppm Au ion (CNT-MoS2), 250 mg/g to 20 ppm Au ion (PAF-1-thiourea), 100 mg/g to 20 ppm Au ion (COP-180) and 500 mg/g to 196.9 ppm Au ion (PTL membrane), respectively. In comparison, rGO showed a significantly higher capacity as shown in Supplementary Fig. 1a and Supplementary Fig. 1b.
Moreover, this exceptional performance of rGO suspensions extends into the ppb and sub-ppb range where no other adsorbent was so far reported to exhibit any discernible extraction of gold ( Supplementary Fig. 1c).  Table 1. For determination of extraction efficiency and capacity to 1 ppb, 20 ppt and 10 ppt gold solution, 0.3 mg rGO was added in 200 mL of gold solution with above concentrations. For 1 ppb gold solution, we obtained ~100 % extraction efficiency measured by inductively coupled plasma mass spectrometry (ICP-MS), which translated into an extraction capacity of ~0.7 mg/g, and similar to higher concentration, XPS analysis showed extracted gold was predominately Au 0 ( Supplementary   Fig. 1c inset). For rGO's adsorption to 20 ppt and 10 ppt gold solution, as ICP-MS approaches its detection limit, the rGO nanosheets after extraction were collected by centrifugation and drop-casted on a Si wafer substrate for XPS analysis. The gold contents that measured at different areas (at least 5 areas) varied from 0.01-0.18 at%. Thus, as a semi-quantitative method, XPS clearly validates significant gold extraction by rGO at ppt level.

Supplementary Note 2. Characterization of graphene oxide and rGO before and after Au extraction
To characterize our graphene-based materials, we used X-ray diffraction (XRD) combined with other analytical techniques, including XPS and Fourier transform infrared (FTIR) spectroscopy (Nicolet iS50). The XRD patterns of GO, rGO before and rGO after Au extraction (denoted below as rGO-Au, 10 ppm [AuCl4]was used) are shown in Supplementary Fig. 4a. The XRD confirmed that GO was reduced by ascorbic acid. Indeed, the ~10° peak known for GO disappeared whereas another peak characteristic of rGO emerged at ~23°. The gold on rGO-Au was found to be metallic as determined from its XRD peaks (XRD peak was fitted according to JCPDS data, No. 04-0784).
The FTIR spectra of GO, rGO, and rGO-Au are shown in Supplementary Fig. 4b. To validate gold ion has been reduced to metallic gold during extraction, thermogravimetric (TG) and differential scanning calorimetry (DSC) were used to analyse rGO sample after 24 hours extraction (rGO-Au-24 h). Supplementary Fig. 4c shows the TG and DSC curves of rGO and KAuCl4.The weight losses of rGO and KAuCl4 during heating were ascribed to the decomposition of rGO and [AuCl4] -Au 0 , respectively. For KAuCl4, such transformation led to an endothermic peak at ~330 o C, which is in agreement with the previous report 25  The Raman spectra in Supplementary Fig. 5a show that the ID/IG ratios of rGO and rGO-Au are 1.06 and 0.94, respectively. The defect density in the carbon materials, especially graphene materials is characterized by LD, the distance between two neighboring defects. Obviously, a higher LD suggests a less defective carbon material 26 . LD could be determined from ID/IG, and generally does not monotonically change with ID/IG. At a small LD, an increase in ID/IG suggests an increased LD. After reaching a maximum, LD further increases with decreased ID/IG. GO and rGO are reported with a small LD that increases with an increased ID/IG. GO and rGO are reported with a small LD that decreases with a decreased ID/IG, therefore, the observed decrement of ID/IG after gold extraction suggested a more defective state of rGO, supporting the electron donation from rGO to gold. In addition, G band of rGO after gold extraction showed a blueshift from 1602 to 1606 cm -1 , confirming a p-doping and electron transfer from rGO to gold 27 .
Supplementary Fig. 6 are the Raman map of G and D bands of rGO before and after the gold extraction at 25 o C and 60 o C respectively. We found that, firstly, because of the existence of gold on the rGO surface, the surface enhanced Raman scattering (SERS) effect emerged. Specifically, ID peak showed an intensity range from 300-1400 for rGO, increased to 1500-2600 after gold extraction, and IG peak increased from 300-1200 to 1400-2200. Secondly, such mapping allowed us to summarize the change of ID/IG before and after gold extraction. In good agreement with Supplementary Fig. 6a, ID/IG decreased from a range of 1.00-1.15 to 0.93-1.02 after extraction, suggesting a more defective rGO after gold extraction, because of the electron donation.
Supplementary Fig. 5b shows the UV-Vis spectra of GO, rGO, and rGO-Au. Compared to GO, the peak at 227 nm corresponding to π → π* transitions of aromatic C-C bonds shifts to 263 nm after reduction, indicating the restoration of the electronic conjugation within the graphene sheets 28 .
After mixing the rGO with [AuCl4] -, i.e. sample rGO-Au, we observed a blueshift of rGO characteristic absorption peak from 263 nm to 232 nm after 24 hr extraction, indicating electron transfer from the graphitic area to [AuCl4]and reducing [AuCl4]to Au 0 , the adsorption peak of Au 0 located at 555 nm, which is typical for gold nanoparticles.  Fig. 7). It can be seen that, even after 2 minutes, gold nanoparticles already appeared, suggesting that the reductive adsorption mechanism kicked in. It was clear that each gold particle has an intraparticle distance between tens nanometers to a few hundred nanometers, this suggested the electron transfer needed for reductive adsorption may only require electron transfer in the sub-micrometre range, so that the interconnected graphene areas of rGO were able to provide electrons and reduce gold ion at its vicinity. To check whether it is metallic gold or KAuCl4 salt adsorption dominated in the early stages, we analysed rGO-Au after 10 minutes extraction (rGO-Au-10 min, 10 ppm gold solution is used) by TG and DSC analysis ( Supplementary Fig. 8). Similar to rGO-Au-24 h, we did not observe the corresponding peak for [AuCl4] -Au 0 for rGO-Au-10 min. This is similar to the behaviour found for rGO-Au after 24 h reduction ( Supplementary Fig. 4d), and confirms that the reductive adsorption mechanism takes place rapidly, at least within less than a few minutes. In addition, TG showed ~56.7 wt% for rGO-Au-10 min, which gives an extraction capacity ~1.2 g/g for 10 min gold extraction, in good agreement with the capacity measured by ICP-MS ( Fig. 1c in the main text).

Supplementary Fig. 8|
TG and DSC curves of KAuCl4 and rGO-Au-10 min measured in air.

Supplementary Note 4. Gold reduction on mechanically exfoliated graphene
To gain further insight into the Au reduction mechanism, we studied the influence of graphene's thickness and morphology on its gold extraction ability. To this end, we prepared pristine graphene crystals by the standard exfoliation technique on top of an oxidized Si wafer 29 . Their thickness (the number of layers, N) was identified using optical contrast 29 . The obtained crystals were then exposed to a 10 ppm KAuCl4 aqueous solution. Supplementary Fig. 9 exemplifies our observations. The SEM image shows a region covered with mono-and bi-layer graphene. After its exposure to the Au solution for 5 minutes, many areas of monolayer graphene became scrolled, warped and folded.
These structural distortions were also observed in bilayer and few-layer regions (Supplementary accurately M for warped areas because of their unknown and varying thickness. However, the SEM contrast suggests that they contained graphene monolayers (and occasionally bilayers) folded only a few times. This allows us to estimate M for warped graphene as  1,000 mg per g of carbon, in agreement with the extraction capacity observed for rGO for short times (Fig. 1c in the main text).
In this respect, it is important to emphasize that rGO also consists of scrolled, wrinkled and folded areas rather than flat graphene.
Next, similar samples containing graphene and graphite were exposed to the same 10 ppm Au solution for 19 hr. Again, Au nanoparticles were found to heavily cover warped areas, but the coverage of flat areas was also denser allowing statistical analysis. The results are summarized in Supplementary Fig. 10 and Fig. 2e. First, Au nanoparticles became noticeably bigger for all N and occasionally could reach up to 100 nm in size. The particles also acquired irregular shapes as shown in Supplementary Fig. 10, suggesting a merger of several smaller particles. The areal Au extraction was found to be highest for monolayers, decaying with increasing N but recovering to mid values for thick graphite crystals. This behaviour is illustrated by micrographs of Supplementary Fig. 10 and quantified in Fig. 2e. We attribute the higher coverage observed for N = 1 to the fact that visibly flat areas of monolayer graphene were not atomically flat but followed the morphology of the oxidized Si wafer. Ripples on graphene were previously shown to be catalytically active 30 .
Accordingly, the high coverage of monolayers could be due to the same effect as seen in Supplementary Fig. 9 for warped graphene. For larger N, crystals became increasingly flat, leading to fewer Au nanoparticles. It remains to be understood why graphite surfaces also contained a reasonably high Au coverage, higher than that on few-layer graphene. To this end, we note that our graphite crystals contained cleavage steps and some folded areas. This allows us to speculate that Au reduction occurred predominantly on the steps and folds (catalytically active features) and then nanoparticles migrated along the atomically flat surfaces of graphite crystals, leading to their relatively uniform coverage. Results of Supplementary Fig. 10 and Fig. 2e yield the extraction capacity M for monolayer graphene of  6,000 mg per gram of graphene, that is, 3 times higher than for rGO in Fig. 1 of the main text. Such enhancement is perhaps not surprising because rGO nanosheets 1) contain oxidized areas (that is, not the entire surface could take part in reduction and it might contribute to the energy barrier for gold reduction as observed in Fig. 2c) and 2) tend to coagulate after initial stages of gold adsorption so that some of the graphene areas become inaccessible to gold ions. To gain the understanding on why warped area of graphene enhance gold extraction behavior, we studied adsorption energy and charge transfer between gold ion and graphene using First-principle calculation ( Supplementary Fig. 11). All calculations were carried out using the Vienna Ab initio Simulation Package (VASP) 31,32 based on density functional theory (DFT) 33,34 with the Perdew-Burke-Ernzerhof functional 35 . As shown in Supplementary Fig. 11a and b, AuCl3 cluster was adopted to represent the valence state of Au 3+ , while (10, 10) carbon nanotube (CNT) was chosen as a similarity of the warped and curved surface of graphene. 661 and 115 supercells for graphene and nanotube were constructed to study the adsorption of Au 3+ . The vacuum layers were set as at least 12 Å to avoid spurious interactions among periodic images. Zero damping DFT-D3 method 36 was applied to describe van der Waals interaction. The adsorption energy was defined as E=ET-EC-EAuCl3, where ET, EC and EAuCl3 are the total energies of the adsorption system, graphene or nanotube supercell, and AuCl3 cluster, respectively.

Supplementary
Our results show that, in contrast to flat graphene, the adsorption energy of gold ion on curved graphene surface is about 0.1 eV lower than that on graphene, indicating its preferred adsorption on the curved graphene surface. After adsorption, the electron transfer process from graphene to gold ion drives the reduction of gold ion to Au 0 . Our calculation shows that, the curved graphene has a Fermi level ~0.3 eV higher than that of flat graphene, this leads to a more significant charge transfer from curved graphene. This is further validated by Bader charge analysis, that we found that the numbers of electrons transferred from curved and flat graphene to gold ion are 0.61 and 0.47, respectively, in good agreement with observed significant gold reductive adsorption on curved surfaces.
To further determine the difference in electron transfer, we also performed gas-phase calculations on cluster models, which can take different charge states. Supplementary Fig. 11c and d show the structural models for Au-adsorbed graphene and CNT clusters, which were saturated with H atoms.
The +3 charge state of the cluster models was realized by artificially setting the number of electrons, and the compensating background charge was included to ensure the convergence of electrostatic energy. After structural relaxation, the Bader charge analysis shows that the number of electrons transferred from CNT and graphene clusters to Au 3+ was 3.03 and 2.81, respectively. Compared to graphene, CNT transferred 0.22 more electrons to Au 3+ , which is consistent with the calculation based on AuCl3 models (0.13 e). Here, we used the idealized charged systems, and a jellium background charge was added to ensure the whole system is neutral. It should be noted that, the jellium charge might introduce spurious states in the vacuum 37  To summarize, our observations for exfoliated graphene suggest that both surface area and thickness are important for efficient Au extraction. The available area is obviously maximal for monolayer graphene, as in rGO's solutions and membranes used in our work. The extraction capacity is negligible for graphite (in terms of gold extracted per gram) and rapidly increases as 1/N with decreasing the graphite thickness N. Moreover, monolayer graphene is also beneficial for Au reduction by speeding up the process on top of uneven and warped areas, which are abundant within rGO nanosheets. In addition, our experiments on exfoliated graphene confirmed that it was pristine graphene areas that were important for Au reduction, and the minority rGO areas that remain oxidized played little role in the process.

Supplementary Note 5. Evaluation of different graphene-based adsorbents
For the rGO reduced by ascorbic acid with different time, we have used XPS, specifically, changes in C/O ratio of resulting rGO, to confirm that control of reduction time can tune the oxidized region of rGO. As shown in Supplementary Fig. 12, pristine GO showed a C/O ratio of 2.2, which has increased to 4.2, 4.7, 5.1, 5.7 for a reduction time of 10 min, 30 min, 1 h, 4 h respectively, as discussed in the previous paper, such increase of C/O ratio was strong evidence for the removal of oxidized region 24,38 .
For the rGO reduced by hydrazine and hydroquinone, commercial graphene (bought from Nanjing XFNANO Materials Tech Co., Ltd.) and expanded graphite, to supplement the main text conclusion, we focused on their zeta potentials ( Supplementary Fig. 12b). All the GO-based materials exhibited negative zeta potentials > |30 mV|. Such values are considered to be sufficient to provide a stable colloid 39 . In contrast, commercial graphene and expanded graphite, both had well-retained graphene areas, as confirmed by a prominent G peak and a very weak D peak from the Raman analysis ( Supplementary Fig. 12c), but they either floated on or settled in the aqueous solution, failed to form a stable colloidal dispersion in water (inset of Supplementary Fig. 12b).
It is interesting to note that hydroquinone-reduced GO showed a lower zeta potential (in the absolute value), which was also accompanied by a lower extraction capacity of this rGO (Fig. 2g), as compared to the characteristics observed for ascorbic acid-and hydrazine-reduced GO. These

Supplementary Note 6. Extraction of gold from seawater
As an initial test for the selectivity of rGO, we measured its uptake of metals from an aqueous solution containing 10 ppm of each Au, Cu, Ni and Pt, using salts KAuCl4, CuCl2, CuSO4, Cu(NO3)2, NiCl2 and K2PtCl4. As shown in Supplementary Fig. 13a, rGO allowed recovery of ~99% of Au from the mixture whereas only ~5% Cu, 1.4% Pt and 1% Ni were adsorbed on rGO. Similar % values were also found using 10 ppm solutions of the individual salts rather than their mixture (inset of Supplementary Fig. 13a), as expected for non-interacting hydrated ions. Not only the metal cationic ions, the above experiments also suggested, there was no noticeable influence of the coexisting anionic ions including Cl -, NO 3-, SO4 2-, [PtCl4]on the gold extraction performance. This was probably because there was no specific interaction for these anions with graphene or oxidized regions. This behaviour suggests that graphene exhibits preferential affinity to gold as compared to the co-existing ions (Supplementary Fig. 13b). To demonstrate the effectiveness of rGO for gold extraction from solutions containing many different salts, we prepared a simulated seawater solution containing sodium, magnesium, calcium and potassium ions in concentrations typical for oceans. Then 100 ppb of gold ions were added to this solution. First, we carried out the standard extraction protocol from the simulated seawater using pH  4. The rGO's uptake of gold was found > 99% but with significant presence of Na, Ca and K ( Supplementary Fig. 14). After adding an extra hour at pH  1 (that is, using protocol 2), the gold uptake increased even further with no noticeable presence of Na and Ca. The remaining K ions (4% uptake after protocol 2) could be removed by washing away the potassium salts adsorbed on rGO by simply rinsing rGO in water. This shows that the proposed extraction protocols can be adapted to many different situations to achieve a highly selective extraction of Au ( Supplementary Fig. 14).

Supplementary
In further experiments, 0.3 mg of rGO was added to 200 mL of the simulated seawater spiked with KAuCl4 to achieve absolutely minute concentrations of gold ions (10 ppt). After 2 days of extraction, the rGO was collected by centrifugation and drop-casted on a Si wafer for XPS. Similar to the ppt level of gold in pure water, we observed varied gold contents (0.01-0.11 at%) at different areas, which translated into an extraction capacity even higher than the theoretical capacity (calculated based on 100 % extraction efficiency), such high gold content in rGO measured by XPS allowed us to estimate a complete extraction to gold solution at ppt level.
Supplementary Fig. 14| Gold extraction from simulated seawater. Highly selective extraction from the seawater with added 100 ppb of gold. Comparison of efficiencies for different extraction protocols (colour coded).

Supplementary Note 7. Gold extraction from e-waste
In our demonstration of e-waste recycling in Fig. 3b, a CPU leachate was diluted to emphasize the superior performance of rGO for extracting even trace amounts of gold and make sure all the gold ions were discharged in the leachate by repeated washing. In real conditions, CPU leachates would contain gold in concentrations from a few to tens of ppm 1,2 . Therefore, we also performed  Fig. 15). The ability to achieve such exclusive gold extraction in the presence of many other ions shows an unambiguous potential of the proposed technology for recycling of e-waste. It showed an absorption peak at ~290 nm, which intensity changed linearly with increasing the gold concentration (bottom inset of Supplementary Fig. 16a). This peak was then used in real time to determine gold concentrations in the filtrate and to calculate the uptake. Supplementary Fig. 16a shows that permeance of the membranes decreased with increasing their thickness, as a higher flow resistance is obviously expected for thicker membranes. On the other hand, the extraction efficiency increased with increasing the membrane thickness, which is also expected because thicker membranes get more rGO nanosheets involved in the extraction process. The thickness-dependent trade-off between efficiency and permeance suggests that the continuous extraction process can be adjusted to reach desirable performance by changing the membrane's thickness. Note that, in the described experiments, we did not try to reach highest extraction efficiencies because of rather high Au concentrations and the limited amount of rGO such that the membranes were unable to adsorb all gold present in the tested solution during its single filtration pass. Next, we filtered a 6.6 L of a dilute [AuCl4]solution (100 ppb) through an rGO membrane (3 cm 2 ; 800 nm thick). After the filtration the membrane was exfoliated from its polymer support and studied by SEM. As shown in Supplementary Fig. 16, many nanoparticles were found on top and inside the rGO membrane. XRD confirmed that they were metallic gold. Burning off the rGO membrane resulted in a deposit containing 95.2 wt% Au, 1.7 wt% Na, 1.67 wt% C, and 1.43 wt% O, as measured by EDS (Supplementary Fig. 16d). The purity of the resulting gold is calculated to be 23 carats. Based on the TG analysis of pristine rGO ( Supplementary Fig. 4c), the small amounts of detected carbon, oxygen and sodium come not from our extraction process but were probably due to the residual ash of rGO and contamination of the gold surface during its SEM analysis.

Continuous extraction from CPU leachates
In this experiment, we used an rGO membrane to filter a diluted CPU leachate containing 100 ppb of Au. This was designed to check the effectiveness of the proposed continuous extraction rather than to deal with real Au leachates having typically much higher concentrations of Au (see above).
Also, we did not carry out this particular experiment in a single filtration step as in Fig. 4. Instead, seven cycles of filtration were used until the 50% permeance was reached ( Supplementary Fig. 17).
After each cycle, the membrane was soaked in concentrated HCl at pH =1. Supplementary Fig. 15 shows the permeance and extraction efficiency over those 7 cycles (140 mL in total was filtrated through). Similar to the case of continuous extraction from solutions containing gold ions only (Fig.   4b), we found that the permeance decreased with each extraction cycle because of the blocking of rGO with metallic gold. After each filtration cycle, we implemented soaking in HCl to desorb coexisting ions from rGO ( Supplementary Fig. 17b). However, this desorption required long time

Recovery of copper from e-waste
After extracting gold from our CPU leachates by continuous filtration, the filtrate contained a significant amount of copper and other coexisting elements. We demonstrate that this copper can